Advanced Algorithms for Next Generation Wide Field-of-View (WFOV) EO/IR Staring Sensor Exploitation
ABSTRACT: The mission of the U.S. Air Force Infrared Space Systems Directorate is to develop, acquire, and sustain space-based infrared surveillance, tracking and targeting capabilities for missile early warning, missile defense, battlespace awareness and technical intelligence. To support this mission, enhanced sensors are being developed for the Space-Based Infrared System (SBIRS) for surveillance applications. The increased numbers of detector elements and improved sensitivity of these next-generation next-generation, wide-field-of-view (WFOV) electro-optic (EO) and infrared (IR) sensors motivates the need for advanced algorithms that can efficiently provide real-time exploitation of large volumes of data using limited processing and bandwidth resources. SciTec has been a leader in the research and development of algorithms to exploit Overhead Persistent Infrared (OPIR) data for enhanced extraction, tracking, and exploitation of low-observable target signatures in a timely manner to provide information that is critical for resolving ambiguities, developing tactical parameters, discriminating events and supporting battlespace awareness and missile defense objectives. SciTec has leveraged these algorithm development experiences to identify an innovative end-to-end processing suite for the rapid detection, extraction, and tracking of dim closely-spaced targets in data from WFOV sensors viewing cluttered scenes. BENEFIT: Our proposed product would satisfy several critical objectives for demonstrating feasibility of innovative algorithmic approaches for providing significant improvements in low-observable, multiple, closely-spaced target detection and state vector estimation using WFOV EO/IR staring sensor data. First, our work builds upon an existing clutter suppression technique that has been developed and tested for autonomous processing of R & D data sources that share many of the attributes of these new systems but extends it for use with higher bandwidth data. Second, our work matures and integrates additional processing techniques to address some of the most challenging low observable problems and address closely space object resolution issues. Finally our work combines significant existing capability with these new developments into an environment for rapid tuning against new data sources.
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